相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Machine Learning Approach for Rapid Estimation of Five-Day Biochemical Oxygen Demand in Wastewater
Panagiotis G. G. Asteris et al.
WATER (2023)
Revealing the nature of metakaolin-based concrete materials using artificial intelligence techniques
Panagiotis G. Asteris et al.
CONSTRUCTION AND BUILDING MATERIALS (2022)
A New Approach to Predict the Fundamental Period of Vibration for Newly-designed Reinforced Concrete Buildings
Sergio Ruggieri et al.
JOURNAL OF EARTHQUAKE ENGINEERING (2022)
Explainable machine learning aided optimization of masonry infilled reinforced concrete frames
Iqra Latif et al.
STRUCTURES (2022)
A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength
Danial Jahed Armaghani et al.
NEURAL COMPUTING & APPLICATIONS (2021)
Soft computing-based models for the prediction of masonry compressive strength
Panagiotis G. Asteris et al.
ENGINEERING STRUCTURES (2021)
Evaluation of the ultimate eccentric load of rectangular CFSTs using advanced neural network modeling
Panagiotis G. Asteris et al.
ENGINEERING STRUCTURES (2021)
Explainable Machine learning on New Zealand strong motion for PGV and PGA
Surendra Nadh Somala et al.
STRUCTURES (2021)
Time period estimation of masonry infilled RC frames using machine learning techniques
Surendra Nadh Somala et al.
STRUCTURES (2021)
New fundamental period formulae for soil-reinforced concrete structures interaction using machine learning algorithms and ANNs
Dewald Z. Gravett et al.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING (2021)
Soft computing based closed form equations correlating L and N-type Schmidt hammer rebound numbers of rocks
Panagiotis G. Asteris et al.
TRANSPORTATION GEOTECHNICS (2021)
A Comparative study of Hyper-Parameter Optimization Tools
Shashank Shekhar et al.
2021 IEEE ASIA-PACIFIC CONFERENCE ON COMPUTER SCIENCE AND DATA ENGINEERING (CSDE) (2021)
Prediction of peak ground acceleration for Himalayan region using artificial neural network and genetic algorithm
Amit Shiuly et al.
ARABIAN JOURNAL OF GEOSCIENCES (2020)
Machine learning and nonlinear models for the estimation of fundamental period of vibration of masonry infilled RC frame structures
Aristotelis E. Charalampakis et al.
ENGINEERING STRUCTURES (2020)
Machine Learning in Python: Main Developments and Technology Trends in Data Science, Machine Learning, and Artificial Intelligence
Sebastian Raschka et al.
INFORMATION (2020)
Neural-Network Based Prediction of Inelastic Response Spectra
Sofiane Hammal et al.
CIVIL ENGINEERING JOURNAL-TEHRAN (2020)
Krill herd algorithm-based neural network in structural seismic reliability evaluation
Panagiotis G. Asteris et al.
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES (2019)
On Incremental Learning for Gradient Boosting Decision Trees
Chongsheng Zhang et al.
NEURAL PROCESSING LETTERS (2019)
Classification complexity assessment for hyper-parameter optimization
Ziyun Cai et al.
PATTERN RECOGNITION LETTERS (2019)
Artificial bee colony-based neural network for the prediction of the fundamental period of infilled frame structures
Panagiotis G. Asteris et al.
NEURAL COMPUTING & APPLICATIONS (2019)
Soft computing-based techniques for concrete beams shear strength
Danial J. Armaghani et al.
3RD INTERNATIONAL CONFERENCE ON STRUCTURAL INTEGRITY (ICSI 2019) (2019)
Feature Selection using Random Forest Classifier for Predicting Prostate Cancer
Mia Huljanah et al.
9TH ANNUAL BASIC SCIENCE INTERNATIONAL CONFERENCE 2019 (BASIC 2019) (2019)
Hyperparameter optimization in learning systems
Razvan Andonie
JOURNAL OF MEMBRANE COMPUTING (2019)
Fundamental period of infilled reinforced concrete frame structures
Panagiotis G. Asteris et al.
STRUCTURE AND INFRASTRUCTURE ENGINEERING (2017)
Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model
Ravinesh C. Deo et al.
ATMOSPHERIC RESEARCH (2017)
Prediction of the Fundamental Period of Infilled RC Frame Structures Using Artificial Neural Networks
Panagiotis G. Asteris et al.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2016)
The FP4026 Research Database on the fundamental period of RC infilled frame structures
Panagiotis G. Asteris
DATA IN BRIEF (2016)
Multivariate adaptive regression splines for analysis of geotechnical engineering systems
W. G. Zhang et al.
COMPUTERS AND GEOTECHNICS (2013)
Evaluation of fundamental period of low-rise and mid-rise reinforced concrete buildings
George D. Hatzigeorgiou et al.
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS (2013)
Structural seismic response versus epicentral distance and natural period: the case study of Boumerdes (Algeria) 2003 earthquake
S. Dorbani et al.
STRUCTURAL ENGINEERING AND MECHANICS (2013)
Are theoretically calculated periods of vibration for skeletal structures error-free?
Sameh S. F. Mehanny
EARTHQUAKES AND STRUCTURES (2012)
Analytical investigation of elastic period of infilled RC MRF buildings
Paolo Ricci et al.
ENGINEERING STRUCTURES (2011)
Parameters affecting the fundamental period of RC buildings with infill walls
Mehmet Metin Kose
ENGINEERING STRUCTURES (2009)
Estimation of the fundamental vibration period of existing RC buildings in turkey utilizing ambient vibration records
Kadir Guler et al.
JOURNAL OF EARTHQUAKE ENGINEERING (2008)
Greedy function approximation: A gradient boosting machine
JH Friedman
ANNALS OF STATISTICS (2001)